WO2021183927A1 - Rapid mobile screening and triage for infections and infection severity - Google Patents
Rapid mobile screening and triage for infections and infection severity Download PDFInfo
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- WO2021183927A1 WO2021183927A1 PCT/US2021/022167 US2021022167W WO2021183927A1 WO 2021183927 A1 WO2021183927 A1 WO 2021183927A1 US 2021022167 W US2021022167 W US 2021022167W WO 2021183927 A1 WO2021183927 A1 WO 2021183927A1
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30024—Cell structures in vitro; Tissue sections in vitro
Definitions
- tests When tests are available, they cannot always differentiate those who must be rushed to a hospital from those who can be sent home or can self-quarantine. The need for rapid information is especially important in transient populations, such as homeless shelters, where caregivers may not be able to find the patient later to provide results. Results must be available patient-side in a matter of seconds. In addition, the equipment needed to provide results must be robust enough to operate in a variety of point- of-care settings including outdoor or drive-through testing facilities. It would be highly desirable to be able to recognize infection severity at early points in its progression in order to allow for tailored intervention to reduce adverse outcomes.
- the present disclosure provides a method of analyzing a blood sample from a subject that includes loading the blood sample into a single chamber; acquiring, via an imaging system, a stack of serial focal plane images of the blood sample from a plurality of fields of view of the chamber; creating a virtual three dimensional image of the blood sample from selected ones of the stacks of serial focal plane images; and analyzing the virtual three dimensional image to identify blood formed elements within the blood sample.
- the plurality of fields of view comprise at least twenty-five fields of view, preferably at least fifty fields of view, and even more preferably at least one hundred fields of view.
- the method is performed by a portable automated microscope apparatus at a location of the subject.
- analyzing the virtual three dimensional image to identify blood formed elements within the blood sample comprises identifying a type and amount of white blood cells, and/or identifying an amount of red blood cells and/or hematocrit, and/or identifying an amount of platelets.
- analyzing the virtual three dimensional image to identify blood formed elements within the blood sample comprises determining numbers and percentage by volume in the blood sample of one or more types of white blood cells.
- the one or more types of white blood cells may be selected from the following: lymphocytes, neutrophils, eosinophils, basophils, monocytes, bands, and immature granulocytes.
- the immature granulocytes may include band neutrophils, metamyelocytes, myelocytes, and blasts.
- analyzing the virtual three dimensional image to identify blood formed elements within the blood sample comprises determining a ratio in the blood sample of two or more types of blood formed elements. Exemplary ratios includes the ratio of neutrophils to lymphocytes, neutrophils to platelets, and lymphocytes to platelets.
- the method of analyzing a blood sample may further include using the determined numbers, percentage by volume, and ratios in the blood sample of the one or more types of formed elements, e.g., white blood cells to output relevant hematology measurands and clinical information, such as likelihood and severity of infection.
- acquiring the stack of serial focal plane images in each field of view comprises focusing the imaging system on an initial focal plane of the blood sample within the respective field of view, and then acquiring images at different focal planes along the Z direction.
- Optical information from at least one image in a stack of images of a first field of view may be used to select optical parameters utilized during the acquiring of a stack of serial focal plane images in a second, subsequent field of view.
- Exemplary optical parameters comprise one or more of the following: exposure time, camera gains, and illumination intensity.
- the chamber comprises at least one metachromatic stain in a dry format
- the imaging system comprises a red-green-blue (RGB) detector sensitive to light across the visible spectrum.
- RGB red-green-blue
- a first stain may be utilized that is configured to enhance cell membrane fluorescence and cytoplasm fluorescence
- a second stain may be utilized that is configured to enhance nuclear fluorescence.
- the independent RGB channels of the RGB detector are used to create the virtual three dimensional image of the blood sample from the selected ones of the stacks of serial focal plane images.
- analyzing the virtual three dimensional image to identify blood formed elements within the blood sample comprises processing the virtual three dimensional image using machine vision segmentation.
- the present disclosure provides a method of managing a subject suspected of having an infection, comprising: a) carrying out the method of analyzing a blood sample as described above; b) classifying the subject as: 1) unlikely to have an infection; 2) likely to have an infection; or 3) likely to have an infection with severe symptoms based on the results of step a); and c) managing the subject based on the results of step b).
- the present disclosure provides a method of managing a subject suspected of having a SARS-CoV2 infection, comprising: a) carrying out the method of analyzing a blood sample as described above; b) classifying the subject as: 1) unlikely to have a SARS-CoV2 infection; 2) likely to have a SARS-CoV2 infection; or 3) likely to have a SARS-CoV2 infection with severe symptoms based on the results of step a); and c) managing the subject based on the results of step b).
- steps a) and b) combined are carried out in less than 2 minutes.
- step a) does not comprise the use of cell surface markers.
- the method does not comprise a step of cell lysis.
- step b) further comprises incorporating the results of additional tests or measurements.
- steps a) and b) are carried out in close proximity to the subject.
- steps a) and b) are carried out in a hospital emergency room, in an ambulance, in a nursing home, or in the subject’s home or workplace.
- step c) comprises sending or keeping the subject home, continuing monitoring of the subject, performing additional tests on the subject, admitting the subject to a hospital, or admitting the subject to a hospital intensive care unit.
- step c) comprises maintaining current treatment, changing treatment, or ending treatment.
- the present disclosure provides a method of managing a subject suspected of having sepsis, comprising: a) carrying out the method of analyzing a blood sample as described above; b) classifying the subject as: 1) unlikely to have sepsis; 2) likely to have sepsis; or 3) likely to have sepsis with severe symptoms based on the results of step a); and c) managing the subject based on the results of step b).
- steps a) and b) combined are carried out in less than 2 minutes.
- step a) does not comprise the use of cell surface markers.
- the method does not comprise a step of cell lysis.
- step b) further comprises incorporating the results of additional tests or measurements.
- steps a) and b) are carried out in close proximity to the subject.
- steps a) and b) are carried out in a hospital emergency room, in an ambulance, in a nursing home, or in the subject’s home or workplace.
- step c) comprises sending or keeping the subject home, continuing monitoring of the subject, performing additional tests on the subject, admitting the subject to a hospital, or admitting the subject to a hospital intensive care unit.
- step c) comprises maintaining current treatment, changing treatment, or ending treatment.
- the present disclosure provides a method of managing a subject having an infection, comprising: a) carrying out the method of analyzing a blood sample as described above at least two times; b) classifying the subject as: 1) no change in the infection; 2) improving of the infection; or 3) worsening of the infection based on the results of step a); and c) managing the subject based on the results of step b).
- steps a) and b) combined are carried out in less than 2 minutes.
- step a) does not comprise the use of cell surface markers.
- the method does not comprise a step of cell lysis.
- step b) further comprises incorporating the results of additional tests or measurements.
- steps a) and b) are carried out in close proximity to the subject. In some embodiments, steps a) and b) are carried out in a hospital emergency room, in an ambulance, in a nursing home, or in the subject’s home or workplace. In some embodiments, step c) comprises sending or keeping the subject home, continuing monitoring of the subject, performing additional tests on the subject, admitting the subject to a hospital, or admitting the subject to a hospital intensive care unit. In some embodiments, step c) comprises maintaining current treatment, changing treatment, or ending treatment.
- the present disclosure provides a method of managing a subject having a SARS-CoV2 infection, comprising: a) carrying out the method of analyzing a blood sample as described above at least two times; b) classifying the subject as: 1) no change in the SARS-CoV2 infection; 2) improving of the SARS-CoV2 infection; or 3) worsening of the SARS-CoV2 infection based on the results of step a); and c) managing the subject based on the results of step b).
- steps a) and b) combined are carried out in less than 2 minutes.
- step a) does not comprise the use of cell surface markers.
- the method does not comprise a step of cell lysis.
- step b) further comprises incorporating the results of additional tests or measurements.
- steps a) and b) are carried out in close proximity to the subject.
- steps a) and b) are carried out in a hospital emergency room, in an ambulance, in a nursing home, or in the subject’s home or workplace.
- step c) comprises sending or keeping the subject home, continuing monitoring of the subject, performing additional tests on the subject, admitting the subject to a hospital, or admitting the subject to a hospital intensive care unit.
- step c) comprises maintaining current treatment, changing treatment, or ending treatment.
- the present disclosure provides a method of managing a subject having sepsis, comprising: a) carrying out the method of analyzing a blood sample as described above at least two times; b) classifying the subject as: 1) no change in the sepsis; 2) improving of the sepsis; or 3) worsening of the sepsis based on the results of step a); and c) managing the subject based on the results of step b).
- steps a) and b) combined are carried out in less than 2 minutes.
- step a) does not comprise the use of cell surface markers.
- the method does not comprise a step of cell lysis.
- step b) further comprises incorporating the results of additional tests or measurements.
- steps a) and b) are carried out in close proximity to the subject.
- steps a) and b) are carried out in a hospital emergency room, in an ambulance, in a nursing home, or in the subject’s home or workplace.
- step c) comprises sending or keeping the subject home, continuing monitoring of the subject, performing additional tests on the subject, admitting the subject to a hospital, or admitting the subject to a hospital intensive care unit.
- step c) comprises maintaining current treatment, changing treatment, or ending treatment.
- the present disclosure provides a method of monitoring a subject for a potential infection, comprising: a) carrying out the method of analyzing a blood sample as described above; b) classifying the subject as: 1) unlikely to have an infection; 2) likely to have an infection; or 3) likely to have an infection with severe symptoms based on the results of step a); and c) managing the subject based on the results of step b).
- the subject has no symptoms of an infection.
- the method is carried out on the subject more than once to monitor for the appearance of an infection.
- steps a) and b) combined are carried out in less than 2 minutes.
- step a) does not comprise the use of cell surface markers.
- the method does not comprise a step of cell lysis.
- step b) further comprises incorporating the results of additional tests or measurements.
- steps a) and b) are carried out in close proximity to the subject.
- steps a) and b) are carried out in a hospital emergency room, in an ambulance, in a nursing home, or in the subject’s home or workplace.
- step c) comprises sending or keeping the subject home, continuing monitoring of the subject, performing additional tests on the subject, admitting the subject to a hospital, or admitting the subject to a hospital intensive care unit.
- step c) comprises maintaining current treatment, changing treatment, or ending treatment.
- the present disclosure provides a method of carrying out a hematology screen of a subject prior to a medical procedure, comprising: a) carrying out the method of analyzing a blood sample as described above; b) classifying the subject as: 1) suitable for the medical procedure; or 2) unsuitable for the medical procedure based on the results of step a); and c) carrying out the medical procedure if the subject is classified as suitable.
- the medical procedure is chemotherapy.
- steps a) and b) combined are carried out in less than 2 minutes.
- step a) does not comprise the use of cell surface markers.
- the method does not comprise a step of cell lysis.
- step b) further comprises incorporating the results of additional tests or measurements.
- steps a) and b) are carried out in close proximity to the subject.
- step c) comprises sending or keeping the subject home, continuing monitoring of the subject, performing additional tests on the subject, admitting the subject to a hospital, or admitting the subject to a hospital intensive care unit.
- step c) comprises maintaining current treatment, changing treatment, or ending treatment.
- the present disclosure provides a portable apparatus, comprising: a processor; a hematology analyzer in communication with the processor; and a tangible, non-transitory memory configured to communicate with the processor, the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations comprising: receiving from the hematology analyzer, a stack of serial focal plane images of a blood sample in a chamber from a plurality of fields of view of the chamber; creating a virtual three dimensional image of the blood sample from selected ones of the stacks of serial focal plane images; and analyzing the virtual three dimensional image to identify blood formed elements within the blood sample.
- analyzing the virtual three dimensional image to identify blood formed elements within the blood sample comprises identifying a type and amount of white blood cells, and/or identifying an amount of red blood cells and/or hematocrit, and/or identifying an amount of platelets.
- analyzing the virtual three dimensional image to identify blood formed elements within the blood sample comprises determining numbers and percentage by volume in the blood sample of one or more types of white blood cells.
- the one or more types of white blood cells may be selected from the following: lymphocytes, neutrophils, eosinophils, basophils, monocytes, bands and immature granulocytes.
- the immature granulocytes may include band neutrophils, metamyelocytes, myelocytes, and blasts.
- analyzing the virtual three dimensional image to identify blood formed elements within the blood sample comprises determining ratio in the blood sample of two or more types of formed elements, e.g., white blood cells, e.g., determining the ratio of neutrophils to lymphocytes, etc.
- the tangible, non-transitory memory further has instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations comprising using the determined numbers, percentage by volume, and ratios in the blood sample of the one or more types of formed elements to determine a likelihood that the subject has an infection and/or a severity of the infection.
- the tangible, non-transitory memory further has instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations comprising using optical information from at least one image in a stack of images of a first field of view to select optical parameters utilized during the acquiring of a stack of serial focal plane images in a second, subsequent field of view.
- Exemplary optical parameters include one or more of the following: exposure time, camera gains, and illumination intensity.
- the chamber comprises at least one metachromatic stain in a dry format
- the imaging system comprises a red-green-blue (RGB) detector sensitive to light across the visible spectrum.
- RGB red-green-blue
- a first stain may be utilized that is configured to enhance cell membrane fluorescence and cytoplasm fluorescence
- a second stain may be utilized that is configured to enhance nuclear fluorescence.
- the independent RGB channels of the RGB detector are used to create the virtual three dimensional image of the blood sample from the selected ones of the stacks of serial focal plane images.
- the present disclosure provides an article of manufacture, comprising: a non-transitory, machine-readable memory having instructions recorded thereon that, when executed on a processor, cause the processor to perform operations comprising: receiving from a hematology analyzer, a stack of serial focal plane images of a subject’s blood sample in a chamber from a plurality of fields of view of the chamber; creating a virtual three dimensional image of the blood sample from selected ones of the stacks of serial focal plane images; and analyzing the virtual three dimensional image to identify blood formed elements within the blood sample.
- the machine readable memory has instructions recorded thereon that, when executed on the processor, cause the processor to identify a type and amount of white blood cells, and/or identify an amount of red blood cells and/or hematocrit, and/or identify an amount of platelets.
- the machine readable memory has instructions recorded thereon that, when executed on the processor, cause the processor to determine numbers and percentage by volume in the blood sample of one or more types of white blood cells.
- the one or more types of white blood cells may be selected from the following: lymphocytes, neutrophils, eosinophils, basophils, monocytes, bands, and immature granulocytes.
- the immature granulocytes may include band neutrophils, metamyelocytes, myelocytes, and blasts.
- analyzing the virtual three dimensional image to identify blood formed elements within the blood sample comprises determining ratio in the blood sample of two or more types of formed elements, e.g., white blood cells, e.g., determining the ratio of neutrophils to lymphocytes, etc.
- the machine readable memory has instructions recorded thereon that, when executed on the processor, cause the processor to determine a likelihood that the subject has an infection and/or a severity of the infection.
- the machine readable memory has instructions recorded thereon that, when executed on the processor, cause the processor to use optical information from at least one image in a stack of images of a first field of view to select optical parameters utilized during the acquiring of a stack of serial focal plane images in a second, subsequent field of view.
- Exemplary optical parameters include one or more of the following: exposure time, camera gains, and illumination intensity.
- Fig.1 is a flow diagram of methods of identifying blood formed elements within a blood sample from a patient and for determining a likelihood of the patient having an infection according to some embodiments of the present invention.
- Fig.2 is a schematic plan view of a portion of an automated microscope cartridge that may be utilized in accordance with various embodiments of the present invention.
- Fig.2A is a cross-sectional view of the cartridge of Fig.2 taken along line 2A-2A.
- Fig.3 is a schematic diagram of a portion of an exemplary portable automated microscope apparatus that may be utilized to identify blood formed elements within a blood sample from a patient according to some embodiments of the present invention.
- Fig.4 is a schematic plan view of a chamber of a microscope cartridge illustrating a plurality of field of views from which stacks of images are acquired in accordance with some embodiments of the present invention.
- Fig.5 is a flow diagram of a method of acquiring a stack of images from each of a plurality of fields of view of a chamber of a microscope cartridge in accordance with some embodiments of the present invention.
- Fig.6 is a schematic view of an image stack that includes a plurality of images acquired along the Z direction from a field of view of a chamber of a microscope cartridge.
- Fig.7 illustrates an exemplary processor and memory of a data processing system that may be used to implement the functions of a portable automated microscope apparatus according to some embodiments of the present invention.
- Fig.8 is an image of a blood sample within a chamber of a cartridge according to embodiments of the present invention and illustrating blood cells therein.
- Fig.9 is an enlarged view of a portion of the image of Fig.8.
- Fig.9A is a cross-sectional view of Fig.9 taken along line 9A-9A.
- Fig.10 is a cross-sectional view of a portion of a chamber of a cartridge illustrating blood formed elements therein.
- Fig.11 schematically illustrates a plurality of images taken along the Z direction of the chamber illustrated in Fig.10.
- Fig.12 illustrates an image of a chamber containing a blood sample wherein the image only shows white blood cells.
- Fig.13 illustrates the image of Fig.12 wherein the brightness has been changed in accordance with embodiments of the present invention such that platelets and hematocrit are visible.
- Figs.14A-14B illustrate blood analysis of cancer patients, showing platelets (Fig. 14A) and hematocrit (Fig.14B).
- Fig. 14A platelets
- Fig.14B hematocrit
- a cell can mean a single cell or a multiplicity of cells.
- and/or refers to and encompasses any and all possible combinations of one or more of the associated listed items, as well as the lack of combinations when interpreted in the alternative (“or”).
- transitional phrase “consisting essentially of” (and grammatical variants) is to be interpreted as encompassing the recited materials or steps and those that do not materially affect the basic and novel characteristic(s) of the claimed invention.
- references to a structure or feature that is disposed “adjacent” another feature can have portions that overlap or underlie the adjacent feature.
- Spatially relative terms such as “under,” “below,” “lower,” “over,” “upper” and the like, may be used herein for ease of description to describe an element’s or feature’s relationship to another element(s) or feature(s) as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is inverted, elements described as “under” or “beneath” other elements or features would then be oriented “over” the other elements or features.
- the exemplary term “under” can encompass both an orientation of over and under.
- the device may otherwise be oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.
- the terms “upwardly,” “downwardly,” “vertical,” “horizontal” and the like are used herein for the purpose of explanation only, unless specifically indicated otherwise. It will be understood that, although the terms first, second, etc., may be used herein to describe various elements, components, regions, layers and/or sections, these elements, components, regions, layers and/or sections should not be limited by these terms. Rather, these terms are only used to distinguish one element, component, region, layer and/or section, from another element, component, region, layer and/or section.
- a first element, component, region, layer or section discussed herein could be termed a second element, component, region, layer or section without departing from the teachings of the present invention.
- the sequence of operations (or steps) is not limited to the order presented in the claims or figures unless specifically indicated otherwise.
- Various embodiments of the present disclosure provide, among other things, a rapid test that can conveniently be run at a location of a subject, e.g., a patient (such as at a hospital emergency room, in an ambulance, at a doctor’s office, at a nursing home, at the subject’s home or workplace, etc.) to determine a likelihood that the subject is likely to have an infection and/or a severe infection.
- the methods of the present invention disclosure can be carried out in an average time of not more than about 120, 90, 60, or 30 seconds. Further, the methods can identify and quantity immature cells, including bands, that are too similar to mature blood cells to be detected be previous hematology analyzers. Moreover, the methods of the present invention can be performed by unskilled personnel, relieving the strain on medical professionals, and flagging those subjects who need more resource-intensive confirmatory testing and/or more immediate or intensive care. With reference to Fig.1, a method of identifying blood formed elements within a blood sample from a subject and using that information to determine a likelihood the subject has an infection is illustrated.
- Blood formed elements refers to the solid components of blood, including cells and cell fragments, and excluding soluble components, small molecules, proteins, etc.
- a blood sample is collected from a patient and loaded into a chamber of an automated microscope cartridge (Block 100).
- a sample of blood may be obtained from a person via any suitable technique with any suitable apparatus, such as a lance, hollow needle, syringe, capillary action chamber, or combination thereof. Less than 10 ⁇ L of whole blood is needed and typically an imaging volume of only 0.5 ⁇ L is needed. Examples of automated microscope cartridges and automated microscope readers that may be adapted to carry out embodiments of the present invention include those described in U.S.
- An exemplary automated microscope reader includes the QSCOUT ® reader commercially available from Advanced Animal Diagnostics (Morrisville, North Carolina, USA).
- a portion of an exemplary microscope cartridge 40 is illustrated in Figs.2 and 2A and includes a bottom portion or base 44a, an optically transparent top portion 44b (a “cover slip” or “window”), a chamber 42 therebetween, and a port (not shown) in fluid communication with that chamber for filling the chamber 42 with a blood sample.
- the chamber 42 is defined by two plates in parallel, spaced apart relationship of between about ten microns and twenty five microns (10 ⁇ - 25 ⁇ ), as indicated by “w” in Fig.2A.
- Spacers C such as glass beads, may be used to maintain the desired spacing between the cover slip 44b and base 44a, according to some embodiments.
- Exemplary cartridges that may be utilized in accordance with embodiments of the present invention are described in U.S. Patent No.4,790,640 which is incorporated herein by reference in its entirety.
- the chamber 42 may include a dry stain mixture D that facilitates visualizing the various cells in the blood sample under epifluorescent microscopy.
- a mixture of two metachromatic fluorescent stains are contained within the chamber 42.
- the first stain maximizes membrane and cytoplasm fluorescence, and the second stain maximizes nuclear fluorescence.
- the stains are provided in a dry format within the chamber 42.
- the apparatus 5 comprises an XYZ stage 10 mounted on an XYZ drive assembly 30.
- a sample cartridge 40 is removably inserted into or engaged by the XYZ stage.
- the optical components of the imaging system (also referred to as an imaging reader) for carrying out epifluorescent microscopy include a light or light source 51, a beam splitter 52, an imaging sensor or camera 54, and an objective lens 56, all configured so that light from the source is directed onto the sample cartridge 40, and light emitted or fluoresced from the sample cartridge is directed to the camera 54.
- the imaging sensor or camera 54 may be any suitable imaging device, such as a CCD/CMOS device, and may detect and produce digital images and/or intensity values of various signals.
- the imaging sensor or camera 54 may include an RGB detector that is sensitive to light across the visible spectrum, and that acquires images through respective RGB channels.
- Filters 58, 59 are provided between the camera and beam splitter, and between the light source and beam splitter, so that the appropriate wavelengths of light are directed onto the sample cartridge, and the appropriate wavelengths of light are directed onto the camera.
- All components including the camera, light, and XYZ drive assembly, are controlled by any suitable controller 80, which may comprise a computer or microprocessor with associated memory units, power, and additional control boards (not always shown) such as an XYZ controller board.
- Embodiments of the present invention include an algorithm for closed loop control of the camera and movement parameters for the XYZ drive assembly while imaging two dimensional slices of the three dimensional chamber 42.
- the sample cartridge 40 containing a blood sample within a chamber 42 thereof is loaded within an automated microscope apparatus and the imaging system of the apparatus acquires a stack of serial focal plane images of the blood sample in each of a plurality of fields of view of the chamber 42 (Block 110).
- the chamber 42 is divided into a matrix of field of views, such as that illustrated in Fig.4.
- a top view of the chamber 42 is schematically divided into one hundred (100) fields of view (FOV).
- the XY coordinates for the FOVs are illustrated and the Z direction is into the paper. Images may be acquired from each of the FOVs by the imaging system in a predetermined pattern.
- images are acquired at a first FOV and then images are acquired from a second FOV, etc., along a predetermined path or pattern.
- Fig.4 illustrates an exemplary pattern P of movement between FOVs that may be utilized.
- various patterns of movement may be utilized to acquire images from the FOVs, and embodiments of the present invention are not limited to the illustrated pattern P.
- Image acquisition at each FOV is illustrated in more detail in Fig.5.
- the imaging system acquires a stack of images taken at respective focal planes along the Z direction, e.g., from the top of the chamber 42 to the bottom of the chamber 42, or from the bottom of the chamber 42 to the top of the chamber 42, or from a medial location of the chamber 42 and on both sides of this medial location.
- the XYZ drive assembly 30 is configured to move the cartridge 40 such that the imaging sensor can acquire images from a first FOV (Block 111).
- the imaging system autofocuses on an initial focal plane in the current FOV (Block 112) and then a series of images are acquired along the Z direction at different focal planes (Block 113).
- the initial focal plane is an upper focal plane and the series of images are acquired along the Z direction at different focal planes moving downward.
- a middle focal plane is an initial focal plane and the series of images are acquired along the Z direction at different focal planes around this middle focal plane.
- the initial focal plane is a lower focal plane and the series of images are acquired along the Z direction at different focal planes moving upward.
- Fig.6 schematically illustrates a plurality of acquired images i 1 – i 10 from different focal planes along the Z direction and are collectively referred to as an image stack.
- Various numbers of images in each FOV may be obtained, such as ten (10) images. However, various numbers of images may be acquired from each field of view without limitation. Moreover, different numbers of images may be acquired from different FOVs.
- the Z datum for collecting the image stack in the current FOV may be dynamically altered based on analysis from previous FOVs, allowing the system to compensate for geometric imperfections like tilt.
- Image acquisition at each FOV is a continuous process and analysis of images in an acquired stack may occur while subsequent image stacks are being acquired. Typically, the best-in-focus Z position is found for every FOV.
- Fig.10 is a cross-sectional view of a portion of a chamber 42 of a cartridge illustrating blood cells therein.
- Fig.11 schematically illustrates a plurality of images that are taken along the Z direction of the chamber illustrated in Fig.10. In Fig.11, twenty one images (i 1 – i 21 ) are indicated as being acquired.
- FIG.9 is an enlarged view of the indicated portion of the image of Fig.8 and shows blood formed elements, e.g., blood cells in greater detail.
- Fig.9 is what the camera sees as images are acquired along the Z direction at that location of the blood sample.
- Fig.9A is a cross-sectional view of the image of Fig.9 as indicated and shows that the diameter of one of the illustrated cells in Fig.9 (i.e., the leftmost cell) is larger than the height of the chamber 42. As such, this leftmost cell is slightly deformed as illustrated in Fig.9A.
- the cell that is second from the left has a diameter that is the same as the height of the chamber 42, and the remaining cell has a respective diameter that is smaller than the height of the chamber 42.
- This information is utilized when constructing the virtual three dimensional image of the cells in a blood sample. Having images at multiple focal planes in a FOV allows for an accurate determination of cell size as well as an accurate determination of the structure of the nucleus of a cell.
- Fig.9A also illustrates platelets and red cells in the form of rouleaux.
- images are saved within a raw Bayer pattern, one value per pixel. The advantages of such image acquisition include reducing disk space for storage and enhanced compression.
- a Bayer pattern dedicates more pixels to green than to red and blue, because the human eye is more sensitive to green. The additional green pixels produce a better color image.
- parameters such as exposure time, camera gains, and illumination intensity for a current FOV may be selected using optical information from the previous FOV.
- embodiments of the present invention provide a closed loop method of identifying optimal exposure time, focus and the like while acquiring image stacks from the FOVs. This facilitates determining the optimal brightness needed to identify objects of interest within the blood sample.
- the imaging system proceeds to acquire stacks of images from each FOV for the chamber 42. Once stacks of images are acquired from each FOV, image stacks from one or more of the FOVs may be discarded. For example, FOVs at the edges of the chamber may be discarded because illumination or other optical properties of the acquired images are below a threshold standard, such as uniformity.
- Image stacks from other FOVs may be discarded because the stain within the chamber at the particular location of the FOV did not perform its function adequately, etc.
- the stacks of images from the remaining FOVs are then used to create a virtual three dimensional image of the blood sample (Block 120, Fig.1).
- the virtual three dimensional image is created via one or more processors associated with the portable automated microscope apparatus 5.
- the three dimensional image is then analyzed to identify blood formed elements within the blood sample (Block 130).
- the three dimensional image is configured to trace objects through the image stacks and can be done for specific blood formed elements.
- the three dimensional image is also created using artificial intelligence (AI) and machine vision segmentation to identify objects from the background in the image stacks.
- AI artificial intelligence
- an AI engine may be given the number of cells of each kind in a blood sample in order to enhance the identification of cells. Moreover, the AI engine can be trained to use different images within a stack to identify types of cells and other formed elements. Furthermore, each of the cell components (membrane, nuclear DNA, cytoplasm and granules) has different fluorescence emission spectra which depend on their chemical composition and their reactivity with the metachromatic stain(s) in the chamber. Accordingly, the emitted fluorescence of cytoplasm, DNA, membrane and granules will be seen differently by each of the RGB channels of the camera 54.
- each XY location for each RGB channel of every stacked image carries information on a cell’s XYZ location as well as the cell’s chemical composition. Moving continuously along the Z direction while capturing a series of stacked images creates a pattern of locations along the Z direction going in and out of focus independently in each of the RGB images, based on their XYZ location and their chemical composition represented by their fluorescence wavelengths.
- Results of blood formed element identification and infection determination may be displayed on a display device of the apparatus 5. Results may additionally be transmitted to another device and/or to a cloud-based data storage system when internet access is available for record keeping and further data analysis.
- a portable microscope apparatus according to embodiments of the present invention can operate within or without cloud access.
- a portable microscope apparatus according to embodiments of the present invention is fully functional as a self-contained apparatus and can be used in circumstances where network/cloud access is limited, e.g., in ambulances, remote locations, etc.
- images of individual cells can be shown on a display, potentially eliminating the need to prepare a manual smear, as done in pathology labs today. This facilitates a “review on the spot”.
- some embodiments of the present invention may include a built-in examination tool (e.g., a “markup tool”).
- a markup tool is software that permits a triage person or other medical professional to request a view of any one of multiple cells of interest to verify that the cells of interest have in fact been accurately identified by the portable automated microscope apparatus.
- a triage person or other medical professional may request a view of any one of multiple cells of interest to verify that the cells of interest have in fact been accurately identified by the portable automated microscope apparatus.
- the combination of 10% bands, tachycardia and confusion may be quite serious and the triage person may want to verify the identified bands are indeed bands to support a management decision about a subject being tested.
- machine learning may be utilized to determine the best chamber volume for a particular blood sample. For example, a small chamber volume may possibly lead to inaccuracy in white blood cell count.
- the use of image stacks in combination with convolutional neural networks allows for a determination of the actual volume of the chamber 42.
- the methods and devices of the present invention provide several advantages over prior hematology analyzers. The methods identify and quantify a larger number of cell types than previous methods, including neutrophils, lymphocytes, monocytes, eosinophils, basophils, platelets, and red blood cells (hematocrit).
- the methods of the invention identify and quantify immature white blood cells, e.g., bands, including band neutrophils, band lymphocytes, band monocytes, band eosinophils, and band basophils.
- the methods also identify and quantify all immature granulocytes, including band neutrophils, metamyelocytes, myelocytes, and blasts.
- the methods also identify and quantify nucleated red cells as well as determine hematocrit.
- the methods of the invention involve tracing of the surface of cells and nuclei in a sample to construct 3-dimensional images of the shape of the cell and nucleus from multiple 2-dimensional images, enabling accurate identification of cell type.
- Fig.12 illustrates an image of a chamber containing a blood sample wherein the image only shows white blood cells.
- Fig.13 illustrates the image of Fig.12 wherein the brightness has been changed in accordance with embodiments of the present invention such that platelets and hematocrit are visible.
- the present methods advantageously can be carried out quickly (less than 2 minutes) using a self- contained portable device that can be brought to the subject at any location and can be operated by non-clinicians to obtain critical information for triaging patients, monitoring treatment effectiveness, screening populations for spread of infection, and other uses.
- the thorough evaluation of blood formed elements in the sample allows one to determine the likelihood that the subject from which the sample was obtained currently has an infection and, additionally, whether the infection is likely to result in severe symptoms.
- SARS-CoV2 infection produces lymphocytopenia in greater than 80% of patients that tested positive for COVID-19 (Guan et al., New Eng. J. Med.382:1708 (2020), incorporated by reference herein in its entirety). This measurement provides a diagnostic accuracy equivalent to a CT scan without the time, cost, and need for facilities and healthcare professionals. A finding of lymphocytopenia detected by the present invention indicates that the subject is likely to be positive for COVID-19.
- NLR neutrophil to lymphocyte ratio
- This triage method is invaluable during a pandemic when emergency rooms are overwhelmed with the number of patients. Further, the methods can be carried out before subjects arrive at the hospital, e.g., at home or in the ambulance, to help manage patients, e.g., to determine which patients should be brought to the hospital and which patients can safely quarantine at home. In addition to triage, the methods of the invention may also be used for patients admitted to the hospital or other medical facilities, e.g., for monitoring of recovery from the infection or the effectiveness of therapy.
- a change in the blood cell pattern towards the pattern for a non-infected subject may be indicative of recovery and guide further management of the subject, e.g., a decrease in therapy, stopping therapy, removal from a ventilator, transfer from the ICU to the general ward, release from the hospital, etc.
- the methods of the invention may also be used for patients that have been discharged from the hospital or are in post-recovery settings, e.g., to identify signs of relapse or worsening conditions that may need follow-up or to return to the hospital.
- the methods of the invention can be used to track the spread of an infectious agent.
- the methods may be carried out in a population (e.g., in a nursing home, meat packing plant, barracks, dormitory, school, stadium) to provide rapid evidence of infected subjects.
- the methods may be carried out repeatedly, e.g., daily or weekly, to prevent or slow spread of the infection.
- the methods may be carried out by a non- clinician, the methods provide a quick and inexpensive way to control the risk of infection.
- the methods of the invention also can be used to track the health status of subject at home or otherwise outside a doctor’s office or medical facility. As the methods may be carried out by those without healthcare training, the methods can be used for home-based monitoring and early notification of health issues such as an infection, e.g., as part of a telemedicine program.
- the methods may provide an indication of when in-person medical examination is needed or when a subject should go to a medical facility for treatment. While the above example is for SARS-CoV2 infection, the methods are applicable to other infectious agents, including viruses, bacteria, and other pathogens, that cause infectious diseases, each of which may produce a signature blood cell pattern that can be detected by the present methods and provide the information needed for decision making and management of patients.
- infectious diseases refers to any disease associated with infection by an infectious agent. Examples of infectious agents include, without limitation, viruses and microorganisms.
- Viruses include, without limitation, Hepadnaviridae including hepatitis A, B, C, D, E, F, G, etc.; Flaviviridae including human hepatitis C virus (HCV), yellow fever virus and dengue viruses; Retroviridae including human immunodeficiency viruses (HIV) and human T lymphotropic viruses (HTLV1 and HTLV2); Herpesviridae including herpes simplex viruses (HSV-1 and HSV-2), Epstein Barr virus (EBV), cytomegalovirus, varicella-zoster virus (VZV), human herpes virus 6 (HHV-6) human herpes virus 8 (HHV-8), and herpes B virus; Papovaviridae including human papilloma viruses; Rhabdoviridae including rabies virus; Paramyxoviridae including respiratory syncytial virus; Reoviridae including rotaviruses; Bunyaviridae including hantaviruses; Fil
- Pathogenic microorganisms include, but are not limited to, Rickettsia, Chlamydia, Mycobacteria, Clostridia, Corynebacteria, Mycoplasma, Ureaplasma, Legionella, Shigella, Salmonella, pathogenic Escherichia coli species, Bordatella, Neisseria, Treponema, Bacillus, Haemophilus, Moraxella, Vibrio, Staphylococcus spp., Streptococcus spp., Campylobacter spp., Borrelia spp., Leptospira spp., Erlichia spp., Klebsiella spp., Pseudomonas spp., Helicobacter spp., and any other pathogenic microorganism now known or later identified (see, e.g., Microbiology, Davis et al, Eds., 4 th ed., Lippincott,
- microorganisms include, but are not limited to, Helicobacter pylori, Chlamydia pneumoniae, Chlamydia trachomatis, Ureaplasma urealyticum, Mycoplasma pneumoniae, Staphylococcus aureus, Streptococcus pyogenes, Streptococcus pneumoniae, Streptococcus viridans, Enterococcus faecalis, Neisseria meningitidis, Neisseria gonorrhoeae, Treponema pallidum, Bacillus anthracis, Salmonella typhi, Vibrio cholera, Pasteurella pestis (Yersinia pestis), Pseudomonas aeruginosa, Campylobacter jejuni, Clostridium difficile, Clostridium botulinum, Mycobacterium tuberculosis, Borrelia burgdorferi, Haemophilus ducreyi
- the methods of the invention may be used to determine the likelihood of sepsis in an infected subject and/or the likely of severe symptoms of sepsis. Elevated band neutrophils, elevated band eosinophils, and thrombocytopenia are all markers of sepsis, and identification of subjects with the same may indicate that the subject should by monitored for sepsis. A combination of two or more sepsis markers may be an indication of increased severity. Given that sepsis severity can increase rapidly, the present methods may be used as a rapid triage method, e.g., in the emergency room, to identify subjects that should not be sent home from the hospital but instead should be monitored for rapid worsening of symptoms.
- one aspect of the invention relates to a method of managing a subject suspected of having an infection, comprising: a) carrying out the blood analysis method of the invention; b) classifying the subject as: 1) unlikely to have an infection; 2) likely to have an infection; or 3) likely to have an infection with severe symptoms based on the results of step a); and c) managing the subject based on the results of step b).
- Another aspect of the invention relates to a method of managing a subject suspected of having a SARS-CoV2 infection, comprising: a) carrying out the blood analysis method of the invention; b) classifying the subject as: 1) unlikely to have a SARS-CoV2 infection; 2) likely to have a SARS-CoV2 infection; or 3) likely to have a SARS-CoV2 infection with severe symptoms based on the results of step a); and c) managing the subject based on the results of step b).
- a further aspect of the invention relates to a method of managing a subject suspected of having sepsis, comprising: a) carrying out the blood analysis method of the invention; b) classifying the subject as: 1) unlikely to have sepsis; 2) likely to have sepsis; or 3) likely to have sepsis with severe symptoms based on the results of step a); and c) managing the subject based on the results of step b).
- Examples of management decisions and steps include, without limitation, sending or keeping the subject home, e.g., with specific instructions of symptoms to watch out for and to return to the emergency room if they appear, continuing monitoring of the subject, e.g., for a few hours, starting intravenous fluids and/or oxygen treatment, performing additional tests on the subject and, optionally, sending the subject home with orders to contact the subject depending on the results of the tests, transporting or airlifting the subject to a hospital, admitting the subject to a hospital, or admitting the subject to a hospital intensive care unit.
- additional steps may include classifying a subject as having potential sepsis or possible sepsis, referring the subject over to a sepsis coordinator, or ordering specific confirmatory tests such as lactate or procalcitonin measurements.
- severe symptoms refers to infection symptoms that require treatment in a hospital, e.g., urgent treatment. Examples include, without limitation, breathing difficulties, organ dysfunction, highly elevated fever, severe tachycardia, low systolic blood pressure, or confusion.
- An additional aspect of the invention relates to a method of managing a subject having an infection, comprising: a) carrying out the blood analysis method of the invention at least two times; b) classifying the subject as: 1) no change in the infection; 2) improving of the infection; or 3) worsening of the infection based on the results of step a); and c) managing the subject based on the results of step b).
- a further aspect of the invention relates to a method of managing a subject having a SARS-CoV2 infection, comprising: a) carrying out the blood analysis method of the invention at least two times; b) classifying the subject as: 1) no change in the SARS-CoV2 infection; 2) improving of the SARS-CoV2 infection; or 3) worsening of the SARS-CoV2 infection based on the results of step a); and c) managing the subject based on the results of step b).
- Another aspect of the invention relates to a method of managing a subject having sepsis, comprising: a) carrying out the blood analysis method of the invention at least two times; b) classifying the subject as: 1) no change in the sepsis; 2) improving of the sepsis; or 3) worsening of the sepsis based on the results of step a); and c) managing the subject based on the results of step b).
- the methods of testing a subject having an infection or sepsis may be carried out by using the methods of the invention two or more times (e.g., 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more times) to monitor for changes in the blood cell pattern of the subject.
- the methods may be repeated at any time interval, e.g., every 1, 2, 3, 4, 5, 6, 9, 12, 18, or 24 hours or more.
- management decisions and steps for current patients include, without limitation, maintaining current treatment, changing treatment (increasing or decreasing), ending treatment, transferring the patient from the ICU to the general ward or from the general ward to the ICU, or releasing the patient from the hospital.
- An additional aspect of the invention relates to a method of monitoring a subject for a potential infection, comprising: a) carrying out the blood analysis method of the invention; b) classifying the subject as: 1) unlikely to have an infection; 2) likely to have an infection; or 3) likely to have an infection with severe symptoms based on the results of step a); and c) managing the subject based on the results of step b).
- the subject is a healthy subject, e.g., having no symptoms of an infection.
- the subject is one that has been exposed or may have been exposed to an infectious subject.
- the subject is part of a population where it is desirable to slow or prevent spread of an infection, e.g., nursing home patients.
- a further aspect of the invention relates to a method of carrying out a hematology screen of a subject prior to a medical procedure, comprising: a) carrying out the blood analysis method of the invention; b) classifying the subject as: 1) suitable for the medical procedure; or 2) unsuitable for the medical procedure based on the results of step a); and c) carrying out the medical procedure if the subject is classified as suitable.
- steps a) and b) combined may be carried out in less than 120 seconds, e.g., less than 105, 90, 75, 60, 45, or 30 seconds.
- step a) does not comprise the use of cell surface markers and the method does not comprise a step of cell lysis.
- Each of the above methods may further comprise incorporating the results of additional tests, factors, or measurements as appropriate for determining the likelihood of infection, sepsis, severity, etc.
- Examples of additional tests, factors, or measurements include, without limitation, blood oxygen level, temperature, organ function measurements, lactate, procalcitonin, alertness, confusion, agitation, tachycardia ,systolic blood pressure, age, body mass index, comorbidities, etc.
- Suitable subjects include mammals.
- the term “mammal” as used herein includes, but is not limited to, humans, primates, non-human primates (e.g., monkeys and baboons), cattle, sheep, goats, pigs, horses, cats, dogs, rabbits, rodents (e.g., rats, mice, hamsters, and the like), etc.
- Human subjects include neonates, infants, juveniles, and adults.
- the subject is “in need of” the methods of the present invention, e.g., because the subject has or is believed at risk for an infection or a disorder associated with an infection (e.g., sepsis) including those described herein.
- the subject is a pediatric or neonatal patient and/or the disorder may be one associated with pediatric or neonatal patient, e.g., multisystem inflammatory syndrome in children (MIS-C).
- MI-C multisystem inflammatory syndrome in children
- a portable automated microscope apparatus according to embodiments of the present invention, or any part(s) or function(s) thereof, may be implemented using hardware, software or a combination thereof and may be implemented in one or more computer systems or other processing systems. Many of the operations may be machine operations or may be conducted or enhanced by AI or machine learning.
- Artificial intelligence may refer generally to the study of agents (e.g., machines, computer-based systems, etc.) that perceive the world around them, form plans, and make decisions to achieve their goals.
- Foundations of AI include mathematics, logic, philosophy, probability, linguistics, neuroscience, and decision theory. Many fields fall under the umbrella of AI, such as computer vision, robotics, machine learning, and natural language processing.
- Useful machines for performing the various embodiments include general purpose digital computers or similar devices.
- Various embodiments of the present invention utilize one or more computer systems capable of carrying out the functionality described herein.
- the computer system(s) includes one or more processors, and can include a display interface that forwards graphics, text, and other data from a communication infrastructure or from a frame buffer (not shown) for display on a display unit.
- Fig.7 illustrates an exemplary processor 200 and memory 202 that is representative of data processing systems that may be used to implement the functions of a portable automated microscope apparatus according to embodiments of the present invention.
- the processor 200 communicates with the memory 202 via an address/data bus 204.
- the processor 200 may be, for example, a commercially available or custom microprocessor.
- the memory 202 is representative of the overall hierarchy of memory devices containing the software and data used to implement various functions of the controller 80 as described herein.
- the memory 202 may include, but is not limited to, the following types of devices: cache, ROM, PROM, EPROM, EEPROM, flash, SRAM, and DRAM.
- the memory 202 may hold various categories of software and data: an operating system 206, an image stack acquisition module 208, a virtual three dimensional image creation module 210, a blood cell identification module 212, and an infection detection and severity module 214.
- the operating system 206 controls operations of one or more data processors that implement the methods performed by a portable automated microscope apparatus according to embodiments of the present invention.
- the operating system 206 may manage the resources of the portable automated microscope apparatus and may coordinate execution of various programs (e.g., the image stack acquisition module 208, the virtual three dimensional image creation module 210, the blood formed elements identification module 212, and the infection detection and severity module 214) by the processor 200.
- the image stack acquisition module 208 comprises logic for acquiring, via the imaging system of the portable automated microscope apparatus, a stack of serial focal plane images of the blood sample in each of a plurality of fields of view of a chamber contained within a microscope cartridge as described above.
- the virtual three dimensional image creation module 210 comprises logic for creating a virtual three dimensional image of the blood sample from selected ones of the stacks of serial focal plane images as described above.
- the blood formed elements identification module 212 comprises logic for analyzing the virtual three dimensional image to identify blood formed elements within the blood sample as described above.
- the infection detection and severity module 214 comprises logic for using the blood formed elements identification information to determine the likelihood that the subject has an infection and a severity of the infection as described above.
- a portable automated microscope apparatus or any of its components may be embodied as a customization of an existing system, an add-on product, a processing apparatus executing upgraded software, a standalone system, a distributed system, a method, a data processing system, a device for data processing, and/or a computer program product (i.e., an article of manufacture).
- any portion of a portable automated microscope apparatus or a module may take the form of a processing apparatus executing code, an internet-based embodiment, an entirely hardware embodiment, or an embodiment combining aspects of the internet, software and hardware.
- the system may take the form of a computer program product on a computer-readable storage medium having computer-readable program code means embodied in the storage medium.
- Any suitable computer-readable storage medium may be utilized, including hard disks, CD-ROM, optical storage devices, magnetic storage devices, and/or the like.
- the portable automated microscope apparatus and methods are described herein with reference to screen shots, block diagrams and flowchart illustrations of methods, apparatus (e.g., systems), and computer program products according to various embodiments. It will be understood that each functional block of the block diagrams and the flowchart illustrations, and combinations of functional blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by computer program instructions.
- These computer program instructions may be loaded onto a general-purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions that execute on the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart block or blocks.
- These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart block or blocks.
- the computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Accordingly, functional blocks of the block diagrams and flowchart illustrations support combinations of means for performing the specified functions, combinations of steps for performing the specified functions, and program instruction means for performing the specified functions.
- Example 1 Three subjects living in the same home were exposed to a COVID-19 contact. Subject 1 showed mild symptoms. COVID-19 tests were collected at a testing location and the subjects were sent home to quarantine and wait for results. The present method was used on the three subjects and produced results in 90 seconds.
- Subject 1 showed lymphocytopenia predictive of a positive result.
- Subjects 2 and 3 showed a normal lymphocyte count.
- Virus tests results a few days later came back positive for subject 1 and negative for subjects 2 and 3.
- the present method was repeated on subject 1, who was showing some symptoms of infection.
- the results showed elevated NLR but the values indicated the case would not be severe.
- Daily monitoring was continued for all 3 subjects.
- Subject 1 did not deteriorate and subjects 2 and 3 continued to show normal lymphocyte counts and remained asymptomatic.
- Repeated testing of subject 1 with the present method showed an increase in lymphocyte count and a decrease in NLR, which correlated with the subject feeling better. After 2 weeks the symptoms disappeared for subject 1 and the lymphocyte count and NLR returned to normal. For subjects 2 and 3 the lymphocyte count and NLR remained normal.
- Example 2 A 12-year-old boy showed up at the emergency room with minor cuts. No major issues were identified and the CBC found nothing abnormal. The attending physican suspected infection or possible sepsis and ordered a manual blood cell differential, which took several hours for results. In the meantime, the subject was sent home but returned to the emergency room 2 days later with severe symptoms and subsequently died of severe septic shock. When the manual blood cell differential results came in it showed 50% bands, predictive of severe sepsis. If the present invention has been available and utilized, the high band count could have been quickly detected and a life might have been saved by keeping the patient in the hospital and treating for sepsis.
- Example 3 Observations of NLR in COVID-19 patients in China and in New York indicate an ability to risk stratify the patients.
- an NLR of ⁇ 3 indicates low risk
- >6 indicates patients that should be observed
- 10-20 indicates patients that should be admitted to the ICU
- >20 indicates low odds of survival.
- Higher risk categories can be used to determine whether to move patients from a nasal cannula to a 100% oxygen face mask or to a ventilator.
- decreases in NLR have been correlated with the ability to remove patients from a ventilator.
- the ability to measure NLR in less than 2 minutes with the present invention provides a substantial improvement over the hours needed for results from a manual blood cell differential.
- Example 4 The methods of the present invention were applied to several hundred subjects waiting in line for a COVID-19 test at locations around the country. Blood samples were obtained and tested. Significant numbers (generally falling within a range of 2%-10%) of subjects were determined to have lymphocytopenia. The percentage of lymphocytopenia correlated well with the ongoing percentage of COVID-19 positive subjects in the region of the testing.
- Example 5 The methods of the present invention were applied to several dozen cancer patients undergoing a hematology screen prior to chemotherapy using a QScout device.
- the methods of the invention identified the platelet count (Fig.14A) and hematocrit (Fig.14A) of each patient, rapidly identifying those patients with low platelets ( ⁇ 50,000-80,000) and low hematocrit (20-30%) that should not proceed with the chemotherapy (circled datapoints).
- Fig.14A platelet count
- Fig.14A hematocrit
- the foregoing is illustrative of the present invention, and is not to be construed as limiting thereof.
- the invention is defined by the following claims, with equivalents of the claims to be included therein.
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8224058B2 (en) * | 2006-07-19 | 2012-07-17 | Hemocue Ab | Measurement apparatus, method and computer program |
US20170161545A1 (en) * | 2015-05-28 | 2017-06-08 | Tokitae Llc | Image analysis systems and related methods |
WO2017168411A1 (en) * | 2016-03-30 | 2017-10-05 | S.D. Sight Diagnostics Ltd | Image processing device for identifying blood parasites |
KR101805152B1 (en) * | 2016-06-14 | 2017-12-06 | 조선대학교산학협력단 | Dynamic parameters based red blood cell membrane fluctuation inspection method and digital holographic microscopy used in the same |
EP3586726A1 (en) * | 2018-06-22 | 2020-01-01 | Université Paris Diderot - Paris 7 | Device for imaging blood vessels |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7151246B2 (en) * | 2001-07-06 | 2006-12-19 | Palantyr Research, Llc | Imaging system and methodology |
DK200801722A (en) * | 2008-12-05 | 2010-06-06 | Unisensor As | Optical sectioning of a sample and detection of particles in a sample |
-
2021
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Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8224058B2 (en) * | 2006-07-19 | 2012-07-17 | Hemocue Ab | Measurement apparatus, method and computer program |
US20170161545A1 (en) * | 2015-05-28 | 2017-06-08 | Tokitae Llc | Image analysis systems and related methods |
WO2017168411A1 (en) * | 2016-03-30 | 2017-10-05 | S.D. Sight Diagnostics Ltd | Image processing device for identifying blood parasites |
KR101805152B1 (en) * | 2016-06-14 | 2017-12-06 | 조선대학교산학협력단 | Dynamic parameters based red blood cell membrane fluctuation inspection method and digital holographic microscopy used in the same |
EP3586726A1 (en) * | 2018-06-22 | 2020-01-01 | Université Paris Diderot - Paris 7 | Device for imaging blood vessels |
Non-Patent Citations (1)
Title |
---|
See also references of EP4118419A4 * |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2023125955A1 (en) * | 2021-12-31 | 2023-07-06 | 深圳迈瑞生物医疗电子股份有限公司 | Blood cell analyzer, method, and use of infection marker parameter |
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